SEO research and content-production agents
Agents automate competitor and SERP research, keyword/content-gap discovery, briefing, drafting, optimization, internal linking, publishing, refreshing, and indexing workflows.
64.3%
Best tweets about Agentic SEO
28 Best Tweets About Agentic SEO (2026)
Explore the best tweets about agentic SEO, featuring autonomous research, content operations, technical audits, workflows, safeguards, and measurable results.
SEO agents and agentic workflows with clear tasks, tools, human oversight, safeguards, operating costs, limitations, and demonstrated outcomes.
- Creators
- 21
- Updated
Original Xholic analysis
What 28 top Agentic SEO posts reveal
The conversation presents agentic SEO as a set of workflows for research, content production, publishing and diagnostics, rather than a replacement for strategy. Posts also describe human review and quality controls, alongside a shift toward structured, transaction-ready information for agentic search and commerce.
- Dominant tone
- Positive
- Median score
- 9.79
- Leading format
- Case Study
- Recent posts
- 35.7%
78.6% of posts
All-time engagement
32.1% of posts
Published in 90 days
Conversation map
The themes creators return to
Agentic search, web access, and protocols
The web shifts from human browsing toward agents that retrieve, evaluate, and act through APIs, structured data, MCP, WebMCP, A2A, UCP, and crawler access.
28.6%
Agent architecture, tools, and shared memory
Persistent skills, specialist subagents, MCP/API connectors, shared knowledge stores, orchestration layers, queues, and model-swappable systems support repeatable SEO operations.
25%
Agentic commerce and transactional visibility
SEO expands to helping shopping and booking agents parse pricing, availability, product feeds, merchant data, reviews, and structured information to recommend or transact.
25%
Automation economics and reported outcomes
Posts quantify faster research and optimization, low per-query or per-workflow costs, reduced manual effort, traffic gains, and client-delivery efficiency.
25%
Answer-engine and AI-search optimization
Workflows target citations and visibility in ChatGPT, Perplexity, Claude, Gemini, AI Overviews, and AI Mode through question research, structured content, and AI visibility tracking.
21.4%
Human oversight, quality gates, and limits
Posts stress that agents accelerate execution but do not replace customer understanding, strategy, editorial judgment, relationship building, or review controls.
21.4%
Search Console diagnostics and live optimization loops
Agents use GSC and other live performance signals to diagnose traffic changes, identify opportunities or decay, prioritize fixes, and continuously refresh content.
21.4%
Tone and stance
Sentiment Positive leads
Author posture Supportive leads
Performance benchmark
- Median likes
- 26
- Median reposts
- 3
- Median replies
- 7
- Median views
- 2.3K
Posts with media make up 64.3% of this collection. Their median all-time score is 15.9, compared with 6.66 for text-only posts.
Format mix
- Case Study 32.1% · score 9.90
- Announcement 28.6% · score 10.5
- Opinion 21.4% · score 6.66
- Tutorial 14.3% · score 36.7
Consensus and debate
Where creators agree, and where they do not
Shared view
Agents automate the SEO operating loop
Posts describe agents researching competitors and SERPs, mapping content, drafting and publishing, then using content gaps and Search Console signals to refresh work. The recurring model is an execution loop rather than a one-off prompt.
Shared view
Live performance data closes the loop
Search Console is positioned as an input for diagnosing losses, finding opportunities and prioritizing recovery work; one workflow combines specialist analyses into an executive report and recovery plan.
Shared view
Architecture matters beyond prompts
Contributors emphasize persistent skills, connectors and reusable decision logic. Shared tools, memory and operating layers are presented as ways to make workflows repeatable instead of starting each task from scratch.
Shared view
Agentic search changes site requirements
Several posts argue that agents retrieve through APIs, feeds and structured data, shifting optimization toward parseable information, crawler access, accurate merchant data and direct action.
Open debate
Autonomy versus human quality gates
One post argues AI can review better than many SEOs while still sending drafts for its author’s review. Others explicitly retain human gates and warn that ungated autonomous content can produce poor indexed output.
Open debate
Execution gains do not replace SEO judgment
The optimistic workflow posts focus on automating research and production, whereas critical voices say AI cannot understand customers, build relationships or replace strategic adaptation and long-term SEO expertise.
Open debate
Commerce opportunity, with operational friction
Agentic commerce is presented as a new visibility and transaction channel, but agents may fail where pricing is hidden or difficult to interpret. Structured information is therefore presented as both an opportunity and a constraint.
What performs
Patterns behind standout posts
Tutorials led the format benchmark
Tutorials had the highest supplied median all-time score, 36.68, versus 9.899 for case studies and 10.53 for announcements. The cited tutorials present workflows with tools, steps or operating-cost claims.
Execution claims produced major outliers
The largest supplied score outliers focused on a marketing-agent stack, a claimed reduction in SEO-research time, and a competitor-to-publishing workflow. Their scores were 963.75, 510.96 and 279.19 respectively.
Costed diagnostics make the case tangible
Specific operating economics appear in practical examples: one GSC agent reports per-query and monthly estimates, while another workflow prices competitor research, page reading and keyword discovery as an approximately eight-cent sequence.
Statistical standouts
- View standout post 1 Score 963.8 · 98.44× median
- View standout post 2 Score 511.0 · 52.19× median
- View standout post 3 Score 279.2 · 28.52× median
- View standout post 4 Score 216.3 · 22.09× median
- View standout post 5 Score 63.7 · 6.51× median
Creator landscape
Who shapes this conversation
The five most represented creators account for 35.7% of the selected posts.
-
1. Aleyda Solis 🕊️
@aleyda
2 posts
-
2. Cody Schneider
@codyschneider
2 posts
-
3. Harshil Tomar
@Hartdrawss
2 posts
-
4. Jan-Willem Bobbink
@jbobbink
2 posts
-
5. Julian Goldie SEO
@JulianGoldieSEO
2 posts
-
6. Marie Haynes
@Marie_Haynes
2 posts
Cody Schneider foregrounds deployable loops
Cody Schneider’s two posts center on end-to-end content operations: competitor analysis and publishing, followed by refreshes using Search Console and content-gap signals; a second post extends the stack across agency delivery.
Aleyda Solis spotlights agentic commerce
Aleyda Solis’ posts focus on the strategic implications of agents interacting through APIs, product feeds and structured data, and on optimization for direct action rather than clicks alone.
Harshil Tomar makes safeguards explicit
Harshil Tomar describes an AEO pipeline with quality scoring and a separate architecture post with a review queue and human gate at every stage, making controls part of the claimed production system.
Since the previous snapshot
What changed since Aug 13, 2026
- 78.6% of the selected posts remained.
- The creator count changed by -4.
- The leading sentiment remained stable.
How this analysis was made
Themes, sentiment, stance, and post format are classified per tweet. All counts, shares, medians, creator concentration, freshness, and performance comparisons are then calculated directly from the published snapshot.
Xholic's all-time score compares engagement while accounting for reach, post age, and creator consistency. It is used for relative comparisons within this collection.
This report analyzes the exact 28-post snapshot shown below. AI identifies editorial categories and drafts explanations; all statistics are calculated from the snapshot, and every narrative claim is checked against cited posts before publication.
Best Agentic SEO tweets
Top Agentic SEO tweets from 21 creators
Ranked 01–28
- 01
@gregisenberg ·
Marketing agents are the NEW coding agents. It's code in the cloud that makes decisions off your live business data on a loop. It researches, acts, reads the results, improves, and goes again. Picture an agent that runs your entire Facebook ad account by itself. It researches your customer's pain points, generates on-brand creative, publishes it, kills the losers, scales the winners, and makes more of whatever's working. We show you the EXACT stack. Perplexity to scrape Reddit for real pain points, Nano Banana for on-brand static creative, a vision model to check it against brand guidelines, HeyGen for AI UGC video, all wired into a loop that reads Facebook's data and reacts. Now point it at a business. What are some startup ideas you can point marketing agents to? WordPress runs 43% of the internet. Take the plugins people already pay for, like Yoast, WooCommerce, and WP Forms, and build the AI-first version of each. Examples: Yoast (~$15M ARR) shows you red and green dots and tells you to fix your SEO yourself. The AI version just does it. Proven demand, no AI-native competition, and thousands of site owner pay agenices $1,000 a month and many wish they'd pay less and got more. Coding agents changed who gets to build software. Marketing agents change who gets to grow a company. Full breakdown on @startupideaspod. Thanks to @codyschneider for the sauce. Will break down more marketing agents if people are interested? Just LMK. Watch. https://t.co/gyQED92aI7 I'm rooting for you and happy growing. I think we've heard a lot about coding agents recently. And we're about to hear a lot more about marketing agents.
Watch video
- 02
- 03
@codyschneider ·
you can just remix all your competitors website content in a weekend now with an SEO agent how find your 10 competitors find their sitemaps build a composite database of all their pages build a content map of what you should write about research what is ranking page one for target kewyords competitors content is targeting use data for seo API to find all this data include a 30 minute transcription of your opinion on the industry in the source material write the articles and landing pages publish all this content in one shot every month refresh the content based on content gap analysis, and the related search console data you're now competing with your competitors on SEO and AI search
- 04
@Charles_SEO ·
What Claude skills are you using for SEO? Here's my FULL, custom built stack for reverse engineering SERPs to building the most detailed briefs you've ever seen... These aren't generic prompts, they're custom Skills I built specifically for how I do SEO, loaded into Claude as permanent tools (Connected to things like Ahrefs MCP) that run every time I need them: 1. SERP Consensus Analyser 2. Competitor Content Consensus 3. OnPage Optimisation 4. Competitor Backlink Analyser 5. Self-Audit QA Gate The key insight most people miss about Claude Skills: They're not prompts... They're persistent, reusable systems with specific methodologies baked in. Every skill has its own file with best practices, output formats, and decision logic with corresponding MCPs/Connectors. I built these over months of iteration! - SERP Consensus → Content Consensus → OnPage Optimization is a full content strategy pipeline. - Competitor Backlink Analyser feeds my link building campaigns. - Self-Audit QA Gate ensures quality control on everything. This is what I mean when I say AI makes good SEOs faster 🙌 It doesn't replace the strategy, it automates the execution of a strategy that took 17 years to develop. What skills are you running? Genuinely curious what other people have built already 👀
- 05
@aleyda ·
💸 Agentic Commerce: What SEOs Need To Consider (ACP & UCP) - Excellent analysis by @alexmoss going through: How SEOs must now include the agent as an additional consideration, taking into account that AI agents don’t browse pages but instead query APIs, parse product feeds, and evaluate structured data. Learn about: * Areas to consider for Agentic Commerce Optimization * https://t.co/toxTERq5bE being The Glue * Testing The Agents * What can you do about it now? More! Check it out: https://t.co/evBXVuRXXB
- 06
@codyschneider ·
if you're a marketing agency owner and trying to reduce headcount you need to be deploying marketing agents they can run facebook ads create statics with nano banana and seed dance 2, both on kie ai upload via marketing api to ad account tun off losers, promote winners, remix winners repeat google ads research keywords using data for seo api upload keywords and create campaign via google ads api negative keywords, move search terms in similar families to ad groups, moving winning keywords to winners campaign SEO / AI search research keywords with dat for seo api research articles with serper api record clients unique perspective as transcript write articles based on transcript and serper research publish via api to your CMS refresh articles based on live search console data and content gap analysis data reporting build data pipeline and data warehouse have your coding agent oneshot dashboards, be able to do conversational analytics to answer client questions and write / send weekly reports automatically if you want to do this more below
- 07
@Marie_Haynes ·
The traditional web of human browsing is ending and being replaced by the Agentic web. Google has outlined several new AI protocols that we need to understand including MCP, A2A and UCP. WebMCP will allow agents to use the functionality of your website without even rendering the pixels on the screen. In this article I share how Google is transforming Search into AI Search and why this is the biggest opportunity in SEO since the invention of the Search engine. https://t.co/4E1VXkvniI
- 08
@jbobbink ·
I wanted to test why the AI in GSC is so useless. So I built a GSC agent with 16 subagents of my own. Weekend mornings are for gaming. Mine just happen to involve Google Search Console. I connected Google's Agent Development Kit and Gemini 2.5 to GSC and built what I call GSC Wizard. Instead of clicking through dashboards, you just ask it questions in plain English: "Why did we lose traffic last month?" or "Show me my top 20 keywords." It runs in two modes. Simple mode uses a single Gemini Flash agent. You get answers in 2 to 5 seconds for about $0.003 per query. Deep analysis mode is where it gets interesting. 9 specialist agents investigate your site in parallel. Regional traffic. Device splits. Brand vs non-brand. Keyword cannibalization. Striking distance opportunities. Bencmarking and Low-CTR pages. Content decay. Query decay. SEO experimentation measurements. Then a synthesis agent connects all the dots into one executive report with root causes, regional breakdowns, and a prioritized recovery plan. Under 15 seconds. Costs: ~$0.04–0.06 For the kind of analysis that used to take me a few hours in spreadsheets or Looker dashboards. The key difference from just dumping data into ChatGPT: the LLM never sees your raw data. The backend processes millions of rows server-side and sends compact summaries. Smart caching through Firestore means no redundant API calls. Estimated cost for personal use: $5 to $15 per month. I have never had this level of diagnostic power at my fingertips. Google gave us an AI chatbot that selects date ranges for you and nobody asked for. Maybe what we actually needed was AI that reads our own data and tells us what to fix. But to be fair, that would be an expensive tool. Open to feedback from fellow SEOs who want to use something like this. What questions would you ask your SEO agent wizard?
- 09
@aleyda ·
🤖 This week Google announced a new user agent just for agents - @Marie_Haynes covered this release in a must read piece: Why Google’s New “Google-Agent” is the Biggest Mindset Shift in SEO History, the web is becoming agentic and why this is the most exciting time to be in SEO: "...it is the biggest opportunity we have seen since the invention of the search engine itself. WebMCP and UCP mean we are no longer just optimizing for clicks; we are optimizing for direct action, frictionless commerce, and automated lead generation." Read: https://t.co/ripghS7O0R
- 10
- 11
@illyism ·
The new Agent A by @ahrefs is a pretty easy way to use the MCP / API I tried this prompt and it made a full PDF report 👇 Let's do a blog SEO audit - grab our top pages filtered on /blog - for each top keyword, grab the volume x cpc to calculate potential max value and sort the most valuable 10 blog posts - for each of those blog posts, check our seo title, description, word count, etc - then grab the top 10 SERP for the keyword, and compare us against higher ranking blog posts and tell me how to improve Need to think of better prompts 🤔
- 12
@Hartdrawss ·
We just built a full AEO pipeline for a US family office. To simply explain; AEO = Answer Engine Optimisation. Instead of ranking on Google, the goal is to get cited inside ChatGPT, Perplexity, Claude and Gemini. Here’s the system we built: - Discovery Layer: Pulled quick-win keywords from Google Search Console (positions 5–20), cross-checked with Keyword Planner, then used Exa + AI to find real questions people are asking AI tools that traditional SEO completely misses - Content Layer: Competitor analysis to find angles others missed → structured briefs → articles written with ICP context + specially formatted Q&A blocks designed for how LLMs cite information → strict 6-dimension quality scoring before publishing. - Indexing Layer: Daily automated publishing with instant cache revalidation so new content is immediately visible to crawlers. - Tracking Layer: Daily GSC sync + dashboard that flags when keywords move, stall, or drop. This is the new SEO. Most agencies are still selling backlinks. What do you think though. is AEO already changing how you think about content?
- 13
- 14
@Hartdrawss ·
we kicked off two $10,000+ client builds this week in spaces most agencies haven't touched yet. here's what the strategy and the architecture actually looked like. AEO pipeline for a US family office: Ahrefs flagged something recently that stopped me mid-scroll - websites with zero traditional SEO indexing are getting cited in AI search results. no backlinks. no domain authority. none of the signals that have mattered for the last decade. we're building directly into that gap. - two models, two jobs. Exa for competitor research, claude sonnet for articles. they don't talk to each other - two api calls stitched by a postgres review queue - couldn't return valid json when content is html - delimiters and regex extraction instead - cron fires daily, one article per call, human review gate at every stage - fully autonomous content in prod without a human gate = garbage indexed on google autonomous lead scoring and outreach agent for a B2B SaaS founder from Norway : most people don't realise twitter's algorithm isn't rule-based like every other platform. it runs on Grok. fully autonomous. that changes what you can reverse engineer from reply data entirely. - grok fast at temp 0.2 for ICP scoring. threshold at 6 to qualify - grok for context pull once the lead is qualified - full conversation history, signals, intent - llama-3.3-70b at temp 0.75 for DM generation using that context - low temp = consistent scoring. high temp = messages that don't all read the same - scores and messages render live over SSE while the stream runs both builds started on paper. not in a terminal. the most interesting decisions this week weren't about which models to pick. they were about where to keep the human in the loop and where not to.
- 15
@johncalhooon ·
New workflow I've been running: 1. Claude researches my competitors → x402agency SEO Agent ($0.0025) 2. Reads their landing pages as markdown → x402agency Reader Agent ($0.003) 3. Finds keywords I'm missing → SEO Agent ($0.075) What it found: - Forbes: "Stripe, Visa, Mastercard Race To Build AI Agent Payment Rails" - Stripe raised $500M at $5B for agent payments - Visa launched a CLI for AI bot payments - "ai agent marketplace" = 880 searches/mo, $8.30 CPC Total: 8 cents. Ahrefs charges $99/mo for this. No logins. No API keys. Just Claude + micropayments. This is what "agentic" actually means... not chatbots with personality, but autonomous tools with wallets.
- 16
@natmiletic ·
Thinking about hiring an agency vs. automating SEO with AI? Here's what AI can do: • Write drafts • Suggest keywords • Speed up research Here's what it can't do: • Understand your actual customers • Build real relationships for links • Pivot strategy when needed Tools amplify talent. They don't replace it.
- 17
@connections8 ·
If I see one more "I replaced my entire SEO agency with 8 prompts" post, I’m going to lose it. 🙃 Let’s be real: The person posting it usually doesn’t work in SEO. They’ve never ranked for a slightly competitive keyword. There is never a long term SEO case study. AI is a helpful tool, not a magic "Rank #1" button. Replacing a team of experts with "AI slop" is a great way to watch your organic traffic pull a vanishing act. 📉 I know as I personally have 30 test websites, where I've been testing heavy with AI for 6+ years. Stick to quality strategy. Leave the magic prompts to the influencers who haven't seen a Search Console dashboard since forever.
- 18
@jbobbink ·
Your entire SEO strategy is based on outdated data. And your favorite keyword tool is the reason why. Every major data provider sells you the same thing: historical search volume. Averages based on months of old clicks and queries. Packaged in pretty graphs that make you feel like you know what's coming next. But you don't: you're looking in the rearview mirror while trying to navigate a highway that changes lanes every week. This is the shift most people miss. The tools we all rely on for keyword research are snapshots of where demand was. Not where it is right now. And definitely not where it's going. Think about it. Ahrefs, Semrush, Google Ads Keyword Planner, data4seo. They all pull from the same well: aggregated historical query data. Updated monthly at best. Sometimes quarterly. That works fine when search behavior moved slowly. It doesn't work when a single viral post, a breaking news story, or a new AI feature can reshape search demand overnight. So I changed my approach. I started building proactive agents that monitor live signals instead. Google Trends in real time. Social conversations on LinkedIn, Reddit, X. News cycles as they break. Comments and questions flooding into helpdesks and support tickets. That's where tomorrow's search volume lives today. Your customers are already telling you what they need. They're asking questions in your helpdesk. They're commenting on your social posts. They're filling out surveys and writing reviews. This is live intent data. Not 90-day-old averages. The SEO teams that will win in 2026 aren't the ones with the best keyword lists. They're the ones who build systems that listen to real-time demand signals and act on them before the competition even opens their keyword tool. You can even use it to automate internal linking. Historical data tells you what happened. Live data tells you what to do next. Stop planning your strategy with last quarter's numbers. Start building agents that predict the next wave before it shows up in Ahrefs.
- 19
@realzachbabcock ·
AI Agentic team setup update: - Most of the day was invested in debugging new features on the Podcast AI SaaS - Built my CEO Agent: Master command layer. Reads everything, routes tasks, builds all agent docs, final QC before anything ships. That’s me. - Built my SaaS Builder Agent: Builds and ships new features on ai SaaS one phase at a time until troubleshooting confirmed - Built my Website Builder Agent — Builds and updates ZachBabcock website One phase at a time. In the queue for tomorrow: - SaaS Maintenance Agent — 24/7 monitoring and bug fixing. Never touches architecture — only repairs and protects. - SaaS CS Agent — Lives inside ai SaaS. Handles user support, onboarding questions, and cancellation prevention. - Website Maintenance Agent — Monitors and repairs ZachBabcock website. Flags issues, protects uptime. - ZachBabcock CS Agent — Lives on ZachBabcock website. Qualifies visitors and routes them to the correct next step — newsletter, ai SaaS - Content Research Agent — Produces the Centralized SEO Brief for any topic across any platform. Feeds everything downstream. - Content Producer Agent — Takes the brief + anchor piece + ACF + recent published examples and outputs platform-ready content for every active channel. - Ghostwriter Agent — Writes long-form originals (blog posts) from scratch in Zach’s voice. Activated when long-form channels launch. - Sales Agent — DMs, texts, call prep, follow-up, and pipeline management. - Market Intel Research Agent — Monitors competitors, tracks market positioning, identifies opportunities. Feeds CEO Agent and Sales Agent. - Finance Intelligence Agent — Daily morning brief: net worth, portfolio, BTC, dividends, buy/sell signals. Briefs only, never executes. When this finished, we start moving at Lightspeed. Some tasks will run 24/7 autonomously. Others will run something like this: 1. Laptop or Phone → CEO Agent: “Start Phase 6 build in SaaS build” 2. CEO Agent gives you the Code/Dispatch prompt 3. You send it via Code/Dispatch 4. Mac builds while you do other work or life Actually pretty simple if you understand systems and workflows. Tedious and detailed but simple. Almost running a fully AI agentic operation. Will update later this week if you’re following
- 20
@samuelthompson ·
real world agent use building personalized sales decks that pull in prospects existing SEO/GEO data we go through last 12 month performance, current rankings, and technical audit with them live on their discovery call great way to make "our SEO isn't working" actually mean something to both our team and the lead then our team goes away and uses the fireflies transcript + this data to build personalized 90 day SEO roadmap total cost = < $3 / lead
- 21
@aaditsh ·
Bots used to be junk traffic. Now they can buy things. Every company has spent money trying to block bots. Captchas, rate limits, fraud detection. For 20 years, the playbook was simple: block everything that isn't human. But AI agents can browse, compare, and buy things on behalf of real people. That makes bot traffic valuable for the first time ever. I keep thinking about this. Your website is designed for a human who decides in 2 seconds whether to stay. An AI agent doesn't care about your hero image or your brand colors. It cares about structured data, clear pricing, and whether your product actually matches what its user asked for (and probably other things about your reviews, ratings etc). SEO was built around ranking for a human searching Google. Soon it'll be about making sure an AI agent picks your product when it's shopping for someone. I don't think most companies are thinking about this yet.
- 22
- 23
@semrush ·
Google announced new agentic capabilities coming to Search – including information agents that monitor the web on a user's behalf and Universal Cart that aggregates products from multiple retailers and services in one place. The bigger shift isn’t the feature set. It’s where Search is heading next: delegated decision-making and transaction execution. Information agents introduce persistent, query-based monitoring. That changes the optimization model. Brands now need to compete not just for discovery, but for continuous AI evaluation as pricing, availability, relevance, and product signals evolve over time. Universal Cart pushes commerce further into aggregated, AI-curated experiences. Instead of competing through isolated storefronts, retailers increasingly compete inside recommendation layers controlled by Search itself. As Google expands agentic experiences, the inputs behind visibility become even more important: structured product data, accurate merchant information, trusted third-party signals, and consistent brand authority across the web. https://t.co/v5yobPZXxz.
- 24
@semrush ·
Google has made agentic restaurant booking through AI Mode globally available. Users can now describe what they want, and Google finds options, checks availability, and takes them straight to booking. The path from search to reservation is now a single interaction. This reflects a wider move toward agentic search, where AI retrieves, evaluates, and composes answers on behalf of users. Here's what you can do to optimize for the agentic era: • Ensure AI crawlers can access your site • Write content that’s easy for AI systems to parse • Clearly and consistently use entities • Manage your brand visibility • Track your AI visibility https://t.co/9z1zqSIPVV.
- 25
@sharyph_ ·
I Automated My 60-Minute Optimization Process to 60 Seconds Every week I spent over an hour optimizing blog posts: → Checking title lengths (under 60 chars) → Writing meta descriptions (155-160 chars exactly) → Creating URL slugs → Writing TL;DR summaries → Converting headings to questions → Adding answer capsules → Fixing hierarchy (H1→H2→H3) → Finding internal links → Writing alt text It was killing me. So I built an AI agent using Claude Code that does all of it. The process now: → Drop in my blog post → Run the agent → Get optimized content in 60 seconds Same quality. Zero manual work. This is what AI is actually for: eliminating tedious work you already know how to do. Not replacing your thinking. Automating your checklist. What repetitive task are you still doing manually that could be automated?
- 26
@Marie_Haynes ·
This week we saw so many things get set up as we transition to a new era of the web - the agentic web. I did something different with my newsletter this week. I asked Gemini to look at the transcripts from my client calls and Search Bar meetings and pull out the actionable topics I have been discussing. Then I used those to write a completely new kind of newsletter. If you don't have time to read the full blog post, here are the important things to know: →Search is becoming an "Agentic Manager": Search engines are shifting from simply providing information to utilizing agents that actually get things done. If your search clicks are dropping, it's not likely because of bad SEO. It's probably because AI Mode and AI Overviews answering questions directly. →Gemini in Chrome is transforming workflows: Deep browser integration now allows users to converse with AI across multiple open tabs. Skills let you save and reuse prompts to automate repetitive tasks directly in your browser. →Google's Antigravity is a massive leap forward: This powerful agent manager is proving incredibly effective for building apps and workflows through simple, conversational prompts. This is not a popular opinion, but I like it better than Claude Code and ChatGPT Codex. →UCP and WebMCP offer a competitive edge: Universal Commerce Protocol (UCP) and WebMCP allow AI agents to natively interact with your website's tools and eCommerce functions. Implementing these early will likely give sites a massive advantage as agentic search becomes the norm. →Website management is becoming AI-driven: The way we build and optimize sites is fundamentally changing. With new AI-native tools (like EmDash and Shopify's AI toolkit) and concepts like Andrej Karpathy's autoresearch, we are moving toward an era where agents can continually test, learn, and improve websites autonomously. Read the full newsletter here: https://t.co/IN1AMDarlk
- 27
@JulianGoldieSEO ·
STOP USING AI AGENTS LIKE SEPARATE CHATBOTS. The real advantage comes when every agent shares the same tools, memory, and operating system. The Agent OS Setup: → Automate SEO content and publish directly to WordPress or Netlify → Generate AI avatar videos, images, and code from one mission control → Connect Gemini Notebook, Higgsfield, Hermes, Claude Code, and other MCP tools The Smart Architecture: ✓ Swap in a new model like Qwen 3.8 Max without rebuilding the entire system ✓ Keep company knowledge inside a local Obsidian vault every agent can access ✓ Let workflows like Hermes Astros automatically log competitor research into memory The result? Your agents stop starting from zero and begin improving from every workflow they run. That is how you build an AI system that compounds instead of another folder full of disconnected tools.
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- 28
@JulianGoldieSEO ·
I BUILT A 4-AGENT SEO MACHINE THAT PUBLISHES RANKING CONTENT IN ONE CLICK One site hit 278 clicks per day. The workflow behind it is the part most SEOs are missing. The Results: → Website 1 grew from zero to 278 clicks per day → Website 2 climbed from zero to 74 clicks per day → Website 3 reached 28 clicks per day and is still growing The System: ✓ Hermes Oracle scans trending news and scores topics by interest and virality ✓ A keyword engine pulls Google Search Console queries getting impressions but no clicks ✓ A 13-step SEO skill writes personalized content using my experiments, dashboards and case studies ✓ Four agents quality-check, publish and submit every URL for indexing The Distribution: → One click deploys unique content across multiple WordPress sites → Internal links, external sources and cross-site references are added automatically → The same keyword becomes an edited video with an AI avatar and B-roll The real advantage is not publishing more AI content. It is combining fresh trends, private Search Console data and original case studies before competitors spot the opportunity.
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